Interactive case file · Mato Grosso, Brazil

Connecting Forest Change with Soybean Production Potential

Explore how dated satellite imagery, model-delineated fields, crop prediction and seasonal vegetation activity connect within one reviewable screening record.

Review the evidence Explore the fields

Satellite comparison with the clearing field outlined in cyan — Cyan identifies the clearing field throughout this page.

349.04 haimage-derived clearing component

334.30 haclearing field

77agricultural fields retained

88.1%soybean model probability for field 3

01 · Evidence sequence

From visible change to a field-level signal

Switch between the computed outputs. Each view represents a distinct step in the screening workflow.

**Dated satellite comparison**Natural-colour satellite imagery from August 2022 and July 2026. The cyan outline is an image-derived screening boundary, not a legal determination.

02 · Interactive field portfolio

Inspect boundaries and computed results together

Select a boundary on the map or a row in the table. Field 3—the clearing field—remains highlighted in cyan.

77-field screening table

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Find field Crop

Some model-delineated field segments overlap. Individual field areas should not be summed as a unique regional land-area estimate.

Interpretation boundary

This is a prioritization screen. It does not establish legal deforestation, ownership, supplier identity, crop yield, harvest volume, shipment history or regulatory compliance. Crop labels are model predictions, and derived boundaries are operational screening units.

Attribution

Contains modified Copernicus Sentinel data 2022, 2025 and 2026.
WorldCereal classification module and Van Tricht et al. (2023).
ESA WorldCover 2021, CC BY 4.0.
Seasonal vegetation implementation adapted from the Sentinel Hub script, CC BY-SA 4.0.
Field boundaries generated by running the unmodified Delineate Anything model locally.